
from random import randint
from tempfile import TemporaryFile

import numpy as np




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     Dict		,    _lowerCamelCase					:     Dict		,    _lowerCamelCase					:     Optional[Any])   ->       List[Any]:






							'''simple docstring'''





							__UpperCamelCase      :  Tuple       =   0
							if start < end:
														__UpperCamelCase      :  List[str]       =   randint(_lowerCamelCase		,    _lowerCamelCase)
														__UpperCamelCase      :  Any       =   a[end]
														__UpperCamelCase      :  Optional[int]       =   a[pivot]
														__UpperCamelCase      :  Any       =   temp

														__UpperCamelCase  ,		__UpperCamelCase      :  Dict       =   _in_place_partition(_lowerCamelCase		,    _lowerCamelCase		,    _lowerCamelCase)
														count += _in_place_quick_sort(_lowerCamelCase		,    _lowerCamelCase		,    p - 1)
														count += _in_place_quick_sort(_lowerCamelCase		,    p + 1		,    _lowerCamelCase)
							return count




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     List[str]		,    _lowerCamelCase					:     Union[str, Any]		,    _lowerCamelCase					:     str)   ->       Dict:






							'''simple docstring'''





							__UpperCamelCase      :  List[Any]       =   0
							__UpperCamelCase      :  str       =   randint(_lowerCamelCase		,    _lowerCamelCase)
							__UpperCamelCase      :  Dict       =   a[end]
							__UpperCamelCase      :  str       =   a[pivot]
							__UpperCamelCase      :  Union[str, Any]       =   temp
							__UpperCamelCase      :  Optional[Any]       =   start - 1
							for index in range(_lowerCamelCase		,    _lowerCamelCase):
														count += 1
														if a[index] < a[end]:  # check if current val is less than pivot value
																					__UpperCamelCase      :  List[Any]       =   new_pivot_index + 1
																					__UpperCamelCase      :  Optional[int]       =   a[new_pivot_index]
																					__UpperCamelCase      :  Tuple       =   a[index]
																					__UpperCamelCase      :  Optional[Any]       =   temp

							__UpperCamelCase      :  Any       =   a[new_pivot_index + 1]
							__UpperCamelCase      :  List[str]       =   a[end]
							__UpperCamelCase      :  Optional[Any]       =   temp
							return new_pivot_index + 1, count


lowercase    :   str						=			TemporaryFile()
lowercase    :   Optional[int]						=			100  # 1000 elements are to be sorted


lowercase				,     lowercase    :   Union[str, Any]						=			0, 1  # mean and standard deviation
lowercase    :   Dict						=			np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('The array is')
print(X)


outfile.seek(0)  # using the same array
lowercase    :   Optional[int]						=			np.load(outfile)
lowercase    :   Any						=			len(M) - 1
lowercase    :   Any						=			_in_place_quick_sort(M, 0, r)

print(
    'No of Comparisons for 100 elements selected from a standard normal distribution'
    'is :'
)




print(z)

import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


lowercase    :   List[str]						=			logging.get_logger(__name__)




class 					lowerCamelCase__				(							__lowercase):




	'''simple docstring'''




	def __init__(   self						:Dict	,  *a						:Tuple	,  **a						:List[Any]		)						->					None:
								warnings.warn(
								    "The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
								    " Please use PerceiverImageProcessor instead."	,  a	,  )
								super().__init__(*a	,  **a		)